Various image retrieval methods have been proposed for retrieving a desired image from a database storing data representing a number of images. These methods can be classified broadly into two types, namely (1) a method in which non-image information such as keywords or dates of photography are correlated with images and retrieval is conducted based upon this non-image information, and (2) a method in which retrieval is conducted based upon the features (luminance or color-difference information, image frequency, histogram, etc.) of the images per se.
The latter method, which is referred to as a similar-image search, presents a certain image to a database and searches the database using a feature of the image as a search key. This method is advantageous in that a user who does not possess special knowledge concerning image processing can be provided with a search interface that is intuitively easy to understand.
When a search is conducted based upon the memory of the user, an accurate match between the actual image and the image remembered by the user is rare. It is desirable, therefore, to conduct a search by presenting the database with an image where the understanding is that the presented image may not be exactly the same as that being sought. With the usual similar-image search method, however, the desired image cannot be retrieved unless image brightness or color tone is reproduced accurately.